Monalisa Banerjee

Work place: Techno India Salt Lake, West Bengal – India



Research Interests: Information-Theoretic Security, Network Security, Network Architecture, Information Security


Dr. Monalisa Banerjee is an Associate Professor in Techno India, Salt Lake, West Bengal, India. She is Ph. D. in Computer Science and Engineering. Her Area of Specialization is Digital Watermarking, Network Security and Authentication. She is working with Techno India for last 14 years as an academician in the Department of Computer Application. She worked as a Research Scholar in Jadavpur University for 4 years; as a Project Staff in Bengal Engineering and Science University, Shibpur and also worked with Electronic Research and Development Center of India (under Govt. of India, Dept. of Electronics) as a Project Engineer.

Author Articles
An Improved DCT based Image Watermarking Robust Against JPEG Compression and Other Attacks

By Soumik Das Monalisa Banerjee Atal Chaudhuri

DOI:, Pub. Date: 8 Sep. 2017

Rapid growth of internet service attains better security of multimedia contents now a days. Heading this problem a DCT-based color image watermarking framework is proposed in this article. Many earlier works have suggested embedding watermark information in the low frequencies of the image to enhance the robustness against JPEG compression because low frequencies hold the most significant information of the image and not affected significantly by the quantization method of JPEG algorithm. Replacement of low-frequency components with watermark directly may incur undesirable degradation to the image quality. To preserve the visual quality of watermarked images, we are proposing a watermarking framework that adjusts the DCT low-frequency coefficients by scaled averaging. The security issue is well-taken care with double secret keys. Experimental result set demonstrates that the embedded watermark can be extracted efficiently from the JPEG-compressed images even after very high compression, re-watermarking, other image processing attacks. The extraction algorithm is blind i.e., neither host image nor the watermark is needed at the time of extraction.

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